Software Engineer - Platform Security
Friendliai
San Francisco, CA · Posted October 22, 2026
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Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about security jobs
- Best cities for security jobs #1 San Francisco (316 openings)
- Best cities for security pay after cost of living #1 San Mateo ($241k)
- Most requested AI skills in security jobs #1 AI tools in daily work (10.8%)
- Employers with the most security jobs #1 Amazon (318 roles)
Pay compared with the market
This listing does not state pay. Across 663 open software engineer listings that state pay, the middle half runs $152,500 to $247,500 and the median is $194,500.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
About the job
FriendliAI is looking for an engineer to architect and build the security foundations of a multi-tenant serverless compute platform running on Kubernetes with hardened container isolation. As a Software Engineer, Platform Security, you will own the security design for both the control plane and data plane, implement guardrails as code, and partner closely with Platform/SRE/Infra teams to ship a secure-by-default developer experience. This is a hands-on builder and architect role.
Key Responsibilities
Design and implement the security architecture for a Kubernetes-based, multi-tenant serverless platform.
Build guardrails as code using Terraform and Helm.
Establish network segmentation and service-mesh policy.
Develop secrets and key management patterns.
Implement runtime detections for containerized workloads.
Design and roll out IAM & workload identity management.
Threat model new features and changes to the overall platform.
Collaborate with engineering to debug production issues, lead post-incident hardening, and automate evidence for compliance controls.
Qualifications
5+ years securing cloud-native platforms with a focus on distributed systems and multi-tenancy.
Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
Strong hands-on experience with AWS (IAM, VPC/networking, logging/monitoring, …) and Kubernetes/container security.
Proficiency with Terraform and Helm.
Experience building or operating runtime detections for containers/functions.
Strong technical background in backend systems, cloud infrastructure, or AI tooling
Clear written and verbal communication; ability to translate pricing/business rules into robust systems.
Preferred Experience
Knative or similar serverless-on-K8s frameworks.
Container hardening and sandboxing.
Policy-as-code and admission policy design at scale.
eBPF-based observability, detections, and signal tuning.
Multi-cloud exposure and cross-cloud identity approaches.
Hands-on contributions to SOC 2 / HIPAA control automation and audit evidence pipelines.
Benefits
A front-row seat to the generative AI infrastructure revolution
Competitive compensation and benefits package
Daily lunch and dinner provided; unlimited snacks and beverages
Health check-up and top-tier hardware support
Flexible working hours and a highly collaborative environment
About us
FriendliAI is building the next-generation AI inference platform that accelerates the deployment of large language and multimodal models with unmatched performance and efficiency. Our infrastructure powers high-throughput, low-latency workloads for global organizations and integrates directly with Hugging Face, providing instant access to over 600,000 open-source models. We are on a mission to deliver the world’s best platform for AI inference.